Objectives: Selective Retina Therapy (SRT) uses microbubble formation (MBF) to target retinal pigment epithelium (RPE) cells selectively while sparing the neural retina and the choroid. Intra- and inter-individual variations of RPE pigmentation makes frequent radiant exposure adaption necessary. Since selective RPE cell disintegration is ophthalmoscopically non-visible, MBF detection techniques are useful to control adequate radiant exposures. It was the purpose of this study to evaluate optoacoustically based MBF detection algorithms.
Methods: Fifteen patients suffering from central serous chorioretinopathy and diabetic macula edema were treated with a SRT laser using a wavelength of 527 nm, a pulse duration of 1.7 µs and a pulse energy ramp (15 pulses, 100 Hz repetition rate). An ultrasonic transducer for MBF detection was embedded in a contact lens. RPE damage was verified with fluorescence angiography.
Results: An algorithm to detect MBF as an indicator for RPE cell damage was evaluated. Overall, 4646 irradiations were used for algorithm optimization and testing. The tested algorithms were superior to a baseline model. A sensitivity/specificity pair of 0.96/1 was achieved. The few false algorithmic decisions were caused by unevaluable signals.
Conclusions: The algorithm can be used for guidance or automatization of microbubble related treatments like SRT or selective laser trabeculoplasty (SLT).
Keywords: Algorithm; Feedback; Lasers in medicine; Ophthalmology; Optoacoustics; RPE; Retina therapy; SRT; Selectivity.
© 2021 The Authors.